KEGG: aci:ACIAD0282
STRING: 62977.ACIAD0282
For the expression of recombinant Acinetobacter Fe(2+)-trafficking proteins, prokaryotic bacterial systems, particularly Escherichia coli, are typically the most effective due to the protein's bacterial origin and relatively simple structure without complex post-translational modifications .
Recommended expression systems based on research findings:
| Expression System | Advantages | Limitations | Recommended For |
|---|---|---|---|
| E. coli | High yield, cost-effective, simple setup | Limited post-translational modifications | Basic structural and functional studies |
| Yeast (S. cerevisiae) | Some eukaryotic modifications, higher folding fidelity | Lower yield than E. coli | Studies requiring some post-translational modifications |
| Insect cells | Better protein folding, moderate modifications | More complex, higher cost | Advanced structural studies |
| Mammalian cells (CHO, BHK) | Extensive processing capabilities | Highest cost, complex protocols | Studies requiring mammalian-like modifications |
For optimal results with E. coli expression of Fe(2+)-trafficking proteins:
Select an appropriate E. coli strain (BL21(DE3) is commonly used for recombinant protein expression)
Optimize codon usage for bacterial expression
Include appropriate affinity tags for purification (His-tag or GST-tag)
Consider fusion with endogenous protein sequences to increase yield
Purification of recombinant Fe(2+)-trafficking proteins typically employs affinity chromatography techniques. Based on established methodologies for similar proteins, the following approaches are recommended:
Affinity Purification Methods:
Polyhistidine–nickel ion affinity chromatography:
Glutathione S-transferase (GST)–glutathione affinity:
Typical purification protocol workflow:
Cell lysis (sonication or chemical lysis buffer)
Clarification (centrifugation at 15,000 × g, 30 min, 4°C)
Affinity chromatography
Size exclusion chromatography for further purification
Concentration determination (Bradford or BCA assay)
Purity assessment via SDS-PAGE (>90% purity is typically achievable)
When investigating the function of Fe(2+)-trafficking proteins in vitro, several experimental designs can be employed. Based on similar studies with other iron-related proteins in Acinetobacter, the following approaches are recommended:
Experimental Design for Fe(2+)-trafficking Protein Function:
For a full factorial design experiment investigating the effects of iron concentration and oxidative stress on protein function:
Example 2×3 Factorial Design:
Factor 1: Iron concentration (levels: deficient, normal, excess)
Factor 2: Oxidative stress (levels: present, absent)
Dependent variable: Protein activity or binding capacity
Controls: Wild-type strain, buffer controls
This design requires 6 experimental conditions with a minimum of 3 replicates per condition .
Real-time tracking of iron trafficking requires sophisticated methodologies. Based on research with similar iron-trafficking systems, the following approaches can be applied:
Real-time Iron Trafficking Monitoring:
Fusion protein- and intein-based fluorescent labeling strategies:
Stopped-flow spectrophotometric studies:
Mass spectrometry:
Example data from a fluorescence quenching experiment tracking iron transfer:
| Time (min) | Fluorescence Intensity (% of initial) | Iron Transfer (%) | Notes |
|---|---|---|---|
| 0 | 100.0 | 0.0 | Baseline |
| 5 | 87.3 | 12.7 | Initial binding |
| 10 | 76.1 | 23.9 | |
| 20 | 62.5 | 37.5 | |
| 30 | 55.2 | 44.8 | |
| 60 | 52.1 | 47.9 | Near equilibrium |
Fe(2+)-trafficking proteins likely contribute significantly to A. baumannii pathogenicity based on the critical role of iron in bacterial virulence. Research findings suggest:
Iron acquisition and virulence correlation:
Iron availability and antibiotic susceptibility:
Methodological approaches to study this relationship:
Gene knockout studies followed by virulence assessment in animal models
Growth inhibition assays under iron limitation with/without antibiotics
Transcriptome analysis comparing wild-type and mutant strains under infection-like conditions
Iron acquisition proteins represent potential vaccine targets, as demonstrated by studies with outer membrane proteins like Omp22, AbOmpA, and DcaP-like protein .
The role of Fe(2+)-trafficking proteins in Fe-S cluster assembly can be investigated using several complementary techniques:
Methodological approaches to study Fe-S cluster assembly:
Fluorescent labeling to track Fe-S cluster transfer:
In vitro reconstitution assays:
Reconstitute Fe-S cluster assembly systems with purified components
Include or exclude the Fe(2+)-trafficking protein
Monitor cluster formation spectroscopically
Protein-protein interaction studies:
Use pull-down assays to identify interaction partners
Confirm interactions via biolayer interferometry or surface plasmon resonance
Map interaction domains through truncation analysis
Sample protocol for Fe-S cluster transfer assay:
Express and purify recombinant Fe(2+)-trafficking protein
Label potential Fe-S cluster acceptor proteins with rhodamine
Prepare [2Fe-2S] cluster-loaded donor proteins
Mix components and monitor fluorescence quenching over time
Validate results using mass spectrometry to confirm cluster transfer
| Component | Experimental Condition | Control 1 (no DTT) | Control 2 (no acceptor) |
|---|---|---|---|
| Donor protein | 10 μM | 10 μM | 10 μM |
| Acceptor protein | 10 μM | 10 μM | - |
| DTT | 5 mM | - | 5 mM |
| Buffer | To volume | To volume | To volume |
| Fe-S transfer rate | 0.08 s⁻¹ | No significant transfer | No significant transfer |
When designing experiments to assess the impact of iron availability on Fe(2+)-trafficking protein expression and function, researchers should consider the following methodological approach:
Full Factorial Experimental Design:
Independent Variables:
Iron concentration (3 levels: iron-depleted, normal, iron-rich)
Growth phase (2 levels: exponential, stationary)
Stress conditions (2 levels: present, absent)
Dependent Variables:
Protein expression level (qRT-PCR, Western blot)
Iron binding activity
Bacterial fitness (growth rate)
Controls:
Wild-type strain without manipulation
Knockout mutant for the Fe(2+)-trafficking protein
Complemented mutant strain
This represents a 3×2×2 full factorial design requiring 12 experimental conditions . For each condition, perform at least three biological replicates and three technical replicates.
Data Table Format for Results:
| Iron Concentration | Growth Phase | Stress Condition | Relative Expression (Mean ± SD) | Iron Binding Activity (% of WT) | Growth Rate (OD600/hr) |
|---|---|---|---|---|---|
| Iron-depleted | Exponential | Absent | |||
| Iron-depleted | Exponential | Present | |||
| Iron-depleted | Stationary | Absent | |||
| Iron-depleted | Stationary | Present | |||
| Normal | Exponential | Absent | |||
| ... | ... | ... | ... | ... | ... |
Based on recent vaccine development research against A. baumannii, researchers designing recombinant Fe(2+)-trafficking proteins as vaccine candidates should consider:
Key Design Considerations:
Antigen Selection and Optimization:
Expression System Selection:
Immunization Protocol Design:
Evaluation Methods:
Expected Immunological Outcomes Based on Similar Studies:
To investigate protein-protein interactions involving the Fe(2+)-trafficking protein, researchers should employ multiple complementary methodologies:
Recommended Methodological Approaches:
In vitro Binding Assays:
Pull-down assays using recombinant tagged proteins
Surface plasmon resonance (SPR) for binding kinetics
Isothermal titration calorimetry (ITC) for thermodynamic parameters
Biolayer interferometry for real-time binding analysis
Structural Studies:
X-ray crystallography of protein complexes
NMR spectroscopy for mapping interaction surfaces
Hydrogen-deuterium exchange mass spectrometry to identify binding regions
In vivo Interaction Studies:
Bacterial two-hybrid system
Co-immunoprecipitation from bacterial lysates
Fluorescence resonance energy transfer (FRET)
Proximity ligation assay
Experimental Protocol for Pull-down Assay:
Express recombinant Fe(2+)-trafficking protein with His-tag
Immobilize on Ni-NTA resin
Prepare bacterial lysate containing potential interaction partners
Incubate immobilized protein with lysate
Wash extensively
Elute bound proteins
Analyze by SDS-PAGE and identify by mass spectrometry
Data Analysis Example:
| Potential Interacting Protein | Molecular Weight (kDa) | Pull-down with Fe(2+)-trafficking protein | Pull-down with control protein | Confidence Score |
|---|---|---|---|---|
| Iron-dependent regulator Fur | 17 | +++ | - | High |
| Siderophore-interacting protein BauF | 45 | ++ | - | Medium |
| Fe-S cluster assembly protein IscS | 40 | +++ | - | High |
| Ferredoxin | 12 | + | - | Low |
| Control protein (BSA) | 66 | - | - | N/A |
Researchers face several methodological challenges when studying Fe(2+)-trafficking proteins in Acinetobacter species:
Current Challenges and Methodological Solutions:
Protein Stability and Solubility Issues:
Iron-Binding Specificity Assessment:
Challenge: Distinguishing specific from non-specific iron binding
Solution: Use multiple negative controls; implement competitive binding assays; validate with multiple techniques
Functional Redundancy:
Challenge: Multiple proteins may have overlapping iron-trafficking functions
Solution: Create multiple gene knockouts; perform epistasis analysis; use systems biology approaches to map functional networks
In vivo Relevance:
Challenge: Connecting in vitro observations to physiological significance
Solution: Develop animal infection models; use tissue culture systems; implement in vivo imaging techniques for iron trafficking
Antibiotic Resistance Correlation:
Based on current knowledge and technological capabilities, several promising research directions emerge:
Future Research Directions:
Systems Biology Approach:
Integration of proteomics, transcriptomics, and metabolomics data
Network analysis to position Fe(2+)-trafficking proteins within iron homeostasis systems
Computational modeling of iron flux through bacterial systems
Structural Biology and Drug Development:
High-resolution structures of Fe(2+)-trafficking proteins
Structure-based drug design targeting these proteins
Development of iron-trafficking inhibitors as novel antimicrobials
Vaccine Development:
Assessment of Fe(2+)-trafficking proteins as vaccine antigens
Design of multi-epitope vaccines incorporating conserved regions
Evaluation in animal models of infection
Host-Pathogen Interactions:
Investigation of how host iron sequestration affects bacterial Fe(2+)-trafficking
Examination of Fe(2+)-trafficking protein expression during infection
Evaluation of role in biofilm formation and persistence
Diagnostic Applications:
Development of detection methods for Fe(2+)-trafficking proteins
Assessment as biomarkers for antibiotic resistance
Point-of-care diagnostic tools based on protein detection
Methodological Framework for Future Studies:
To address these future directions, researchers should implement:
Interdisciplinary collaborations (microbiology, structural biology, immunology)
Translational research approaches (bench-to-bedside)
Advanced imaging techniques for real-time tracking
Machine learning for data integration and prediction
CRISPR-Cas9 gene editing for precise genetic manipulation